scholarly journals Smoking and the risk for bipolar disorder: evidence from a bidirectional Mendelian randomisation study

2019 ◽  
pp. 1-7 ◽  
Author(s):  
Jentien M. Vermeulen ◽  
Robyn E. Wootton ◽  
Jorien L. Treur ◽  
Hannah M. Sallis ◽  
Hannah J. Jones ◽  
...  

BackgroundThere is increasing evidence that smoking is a risk factor for severe mental illness, including bipolar disorder. Conversely, patients with bipolar disorder might smoke more (often) as a result of the psychiatric disorder.AimsWe conducted a bidirectional Mendelian randomisation (MR) study to investigate the direction and evidence for a causal nature of the relationship between smoking and bipolar disorder.MethodWe used publicly available summary statistics from genome-wide association studies on bipolar disorder, smoking initiation, smoking heaviness, smoking cessation and lifetime smoking (i.e. a compound measure of heaviness, duration and cessation). We applied analytical methods with different, orthogonal assumptions to triangulate results, including inverse-variance weighted (IVW), MR-Egger, MR-Egger SIMEX, weighted-median, weighted-mode and Steiger-filtered analyses.ResultsAcross different methods of MR, consistent evidence was found for a positive effect of smoking on the odds of bipolar disorder (smoking initiation ORIVW = 1.46, 95% CI 1.28–1.66, P = 1.44 × 10−8, lifetime smoking ORIVW = 1.72, 95% CI 1.29–2.28, P = 1.8 × 10−4). The MR analyses of the effect of liability to bipolar disorder on smoking provided no clear evidence of a strong causal effect (smoking heaviness betaIVW = 0.028, 95% CI 0.003–0.053, P = 2.9 × 10−2).ConclusionsThese findings suggest that smoking initiation and lifetime smoking are likely to be a causal risk factor for developing bipolar disorder. We found some evidence that liability to bipolar disorder increased smoking heaviness. Given that smoking is a modifiable risk factor, these findings further support investment into smoking prevention and treatment in order to reduce mental health problems in future generations.Declaration of interestW.v.d.B received fees in the past 3 years from Indivior, C&A Pharma, Opiant and Angelini. G.M.G. is a National Institute for Health Research (NIHR) Emeritus Senior Investigator, holds shares in P1vital and has served as consultant, advisor or CME speaker in the past 3 years for Allergan, Angelini, Compass Pathways, MSD, Lundbeck (/Otsuka and /Takeda), Medscape, Minervra, P1Vital, Pfizer, Sage, Servier, Shire and Sun Pharma.

2019 ◽  
Author(s):  
Jentien Vermeulen ◽  
Robyn Wootton ◽  
Jorien Treur ◽  
Hannah Sallis ◽  
Hannah Jones ◽  
...  

There is increasing evidence that smoking is a risk factor for severe mental illness, including bipolar disorder. Conversely, patients with bipolar disorder might smoke more (often) as a result of the psychiatric disorder. We aimed to investigate the direction and causal nature of the relationship between smoking and bipolar disorder we conducted a bidirectional Mendelian randomization (MR) study. Publicly available summary statistics from genome-wide association studies on bipolar disorder, smoking initiation, smoking heaviness, smoking cessation and lifetime smoking (i.e., a compound measure of heaviness, duration and cessation). We applied multiple analytical methods with different, orthogonal assumptions to triangulate results, including inverse-variance weighted (IVW), MR-Egger or Egger SIMEX, weighted median, weighted mode, and Steiger filtered analyses. Across different methods of MR, consistent evidence was found for a positive effect of smoking on the odds of bipolar disorder (smoking initiation ORIVW=1.46, 95% CI=1.28-1.66, P=1.44x10-8, lifetime smoking ORIVW=1.72, 95% CI=1.29-2.28, P=1.8x10-4). The MR analyses of the liability of bipolar disorder on smoking provided no clear evidence of a strong causal effect (smoking heaviness betaIVW=0.028, 95% CI= 0.003-0.053, P=2.9x10-2). These findings suggest that smoking initiation and lifetime smoking are likely to be a causal risk factor for developing bipolar disorder. We found some evidence that liability to bipolar disorder increased smoking heaviness. Given that smoking is a modifiable risk factor, these findings further support investment into smoking prevention and treatment in order to reduce mental health problems in future generations.


2019 ◽  
Vol 50 (14) ◽  
pp. 2435-2443 ◽  
Author(s):  
Robyn E. Wootton ◽  
Rebecca C. Richmond ◽  
Bobby G. Stuijfzand ◽  
Rebecca B. Lawn ◽  
Hannah M. Sallis ◽  
...  

AbstractBackgroundSmoking prevalence is higher amongst individuals with schizophrenia and depression compared with the general population. Mendelian randomisation (MR) can examine whether this association is causal using genetic variants identified in genome-wide association studies (GWAS).MethodsWe conducted two-sample MR to explore the bi-directional effects of smoking on schizophrenia and depression. For smoking behaviour, we used (1) smoking initiation GWAS from the GSCAN consortium and (2) we conducted our own GWAS of lifetime smoking behaviour (which captures smoking duration, heaviness and cessation) in a sample of 462690 individuals from the UK Biobank. We validated this instrument using positive control outcomes (e.g. lung cancer). For schizophrenia and depression we used GWAS from the PGC consortium.ResultsThere was strong evidence to suggest smoking is a risk factor for both schizophrenia (odds ratio (OR) 2.27, 95% confidence interval (CI) 1.67–3.08, p < 0.001) and depression (OR 1.99, 95% CI 1.71–2.32, p < 0.001). Results were consistent across both lifetime smoking and smoking initiation. We found some evidence that genetic liability to depression increases smoking (β = 0.091, 95% CI 0.027–0.155, p = 0.005) but evidence was mixed for schizophrenia (β = 0.022, 95% CI 0.005–0.038, p = 0.009) with very weak evidence for an effect on smoking initiation.ConclusionsThese findings suggest that the association between smoking, schizophrenia and depression is due, at least in part, to a causal effect of smoking, providing further evidence for the detrimental consequences of smoking on mental health.


2018 ◽  
Vol 49 (13) ◽  
pp. 2197-2205 ◽  
Author(s):  
Hannah M. Sallis ◽  
George Davey Smith ◽  
Marcus R. Munafò

AbstractBackgroundDespite the well-documented association between smoking and personality traits such as neuroticism and extraversion, little is known about the potential causal nature of these findings. If it were possible to unpick the association between personality and smoking, it may be possible to develop tailored smoking interventions that could lead to both improved uptake and efficacy.MethodsRecent genome-wide association studies (GWAS) have identified variants robustly associated with both smoking phenotypes and personality traits. Here we use publicly available GWAS summary statistics in addition to individual-level data from UK Biobank to investigate the link between smoking and personality. We first estimate genetic overlap between traits using LD score regression and then use bidirectional Mendelian randomisation methods to unpick the nature of this relationship.ResultsWe found clear evidence of a modest genetic correlation between smoking behaviours and both neuroticism and extraversion. We found some evidence that personality traits are causally linked to certain smoking phenotypes: among current smokers each additional neuroticism risk allele was associated with smoking an additional 0.07 cigarettes per day (95% CI 0.02–0.12, p = 0.009), and each additional extraversion effect allele was associated with an elevated odds of smoking initiation (OR 1.015, 95% CI 1.01–1.02, p = 9.6 × 10−7).ConclusionWe found some evidence for specific causal pathways from personality to smoking phenotypes, and weaker evidence of an association from smoking initiation to personality. These findings could be used to inform future smoking interventions or to tailor existing schemes.


2020 ◽  
Author(s):  
Tom C. Russ ◽  
Sarah E. Harris ◽  
G. David Batty

ABSTRACTDementia is a major global public health concern and in addition to recognised risk factors there is emerging evidence that poorer pulmonary function is linked with subsequent dementia risk. However, it is unclear if this observed association is causal or whether it might result from confounding. Therefore, we present the first two-sample Mendelian randomisation study of the association between pulmonary function and Alzheimer dementia using the most recent genome-wide association studies to produce instrumental variables for both. We found no evidence of a causal effect of reduced Forced Expiratory Volume in 1 second (FEV1) or Forced Vital Capacity (FVC) on Alzheimer dementia risk (both P>0.35). However, the FEV1/FVC ratio was associated with Alzheimer dementia risk with, in fact, superior function predicting an increased dementia risk (OR 1.12, 95%CI 1.02-1.23; P=0.016) which may result from survivor bias. While we can conclude that there is no causal link between impaired pulmonary function and Alzheimer dementia, our study sheds less light on potential links with other types of dementia.


2020 ◽  
Author(s):  
Ruth E Mitchell ◽  
Kirsty Bates ◽  
Robyn E Wootton ◽  
Adil Harroud ◽  
J. Brent Richards ◽  
...  

AbstractThe causes of multiple sclerosis (MS) remain unknown. Smoking has been associated with MS in observational studies and is often thought of as an environmental risk factor. We used two-sample Mendelian Randomization (MR) to examined whether this association is causal using genetic variants identified in genome-wide association studies (GWAS) as associated with smoking. We assessed both smoking initiation and lifetime smoking behaviour (which captures smoking duration, heaviness and cessation). There was very limited evidence for a meaningful effect of smoking on MS susceptibility was measured using summary statistics from the International Multiple Sclerosis Genetics Consortium (IMSGC) meta-analysis, including 14,802 cases and 26,703 controls. There was no clear evidence for an effect of smoking on the risk of developing MS (smoking initiation: odds ratio [OR] 1.03, 95% confidence interval [CI] 0.92-1.61; lifetime smoking: OR 1.10, 95% CI 0.87-1.40). These findings suggest that smoking does not have a detrimental consequence on MS susceptibility. Further work is needed to determine the causal effect of smoking on MS progression.


2020 ◽  
pp. 1-6
Author(s):  
Jianhua Chen ◽  
Ruirui Chen ◽  
Siying Xiang ◽  
Ningning Li ◽  
Chengwen Gao ◽  
...  

Background The link between schizophrenia and cigarette smoking has been well established through observational studies. However, the cause–effect relationship remains unclear. Aims We conducted Mendelian randomisation analyses to assess any causal relationship between genetic variants related to four smoking-related traits and the risk of schizophrenia. Method We performed a two-sample Mendelian randomisation using summary statistics from genome-wide association studies (GWAS) of smoking-related traits and schizophrenia (7711 cases, 18 327 controls) in East Asian populations. Single nucleotide polymorphisms (SNPs) correlated with smoking behaviours (smoking initiation, smoking cessation, age at smoking initiation and quantity of smoking) were investigated in relation to schizophrenia using the inverse-variance weighted (IVW) method. Further sensitivity analyses, including Mendelian randomisation-Egger (MR-Egger), weighted median estimates and leave-one-out analysis, were used to test the consistency of the results. Results The associated SNPs for the four smoking behaviours were not significantly associated with schizophrenia status. Pleiotropy did not inappropriately affect the results. Conclusions Cigarette smoking is a complex behaviour in people with schizophrenia. Understanding factors underlying the observed association remains important; however, our findings do not support a causal role of smoking in influencing risk of schizophrenia.


2011 ◽  
Vol 21 (3) ◽  
pp. 223-242 ◽  
Author(s):  
Tom M Palmer ◽  
Debbie A Lawlor ◽  
Roger M Harbord ◽  
Nuala A Sheehan ◽  
Jon H Tobias ◽  
...  

Mendelian randomisation analyses use genetic variants as instrumental variables (IVs) to estimate causal effects of modifiable risk factors on disease outcomes. Genetic variants typically explain a small proportion of the variability in risk factors; hence Mendelian randomisation analyses can require large sample sizes. However, an increasing number of genetic variants have been found to be robustly associated with disease-related outcomes in genome-wide association studies. Use of multiple instruments can improve the precision of IV estimates, and also permit examination of underlying IV assumptions. We discuss the use of multiple genetic variants in Mendelian randomisation analyses with continuous outcome variables where all relationships are assumed to be linear. We describe possible violations of IV assumptions, and how multiple instrument analyses can be used to identify them. We present an example using four adiposity-associated genetic variants as IVs for the causal effect of fat mass on bone density, using data on 5509 children enrolled in the ALSPAC birth cohort study. We also use simulation studies to examine the effect of different sets of IVs on precision and bias. When each instrument independently explains variability in the risk factor, use of multiple instruments increases the precision of IV estimates. However, inclusion of weak instruments could increase finite sample bias. Missing data on multiple genetic variants can diminish the available sample size, compared with single instrument analyses. In simulations with additive genotype-risk factor effects, IV estimates using a weighted allele score had similar properties to estimates using multiple instruments. Under the correct conditions, multiple instrument analyses are a promising approach for Mendelian randomisation studies. Further research is required into multiple imputation methods to address missing data issues in IV estimation.


Author(s):  
Emma L Anderson ◽  
Rebecca C Richmond ◽  
Samuel E Jones ◽  
Gibran Hemani ◽  
Kaitlin H Wade ◽  
...  

Abstract Background It is established that Alzheimer’s disease (AD) patients experience sleep disruption. However, it remains unknown whether disruption in the quantity, quality or timing of sleep is a risk factor for the onset of AD. Methods We used the largest published genome-wide association studies of self-reported and accelerometer-measured sleep traits (chronotype, duration, fragmentation, insomnia, daytime napping and daytime sleepiness), and AD. Mendelian randomization (MR) was used to estimate the causal effect of self-reported and accelerometer-measured sleep parameters on AD risk. Results Overall, there was little evidence to support a causal effect of sleep traits on AD risk. There was some suggestive evidence that self-reported daytime napping was associated with lower AD risk [odds ratio (OR): 0.70, 95% confidence interval (CI): 0.50–0.99). Some other sleep traits (accelerometer-measured ‘eveningness’ and sleep duration, and self-reported daytime sleepiness) had ORs of a similar magnitude to daytime napping, but were less precisely estimated. Conclusions Overall, we found very limited evidence to support a causal effect of sleep traits on AD risk. Our findings provide tentative evidence that daytime napping may reduce AD risk. Given that this is the first MR study of multiple self-report and objective sleep traits on AD risk, findings should be replicated using independent samples when such data become available.


2020 ◽  
Author(s):  
Solal Chauquet ◽  
Michael O’Donovan ◽  
James Walters ◽  
Naomi Wray ◽  
Sonia Shah

ABSTRACTBackgroundThere is growing evidence from observational studies that drugs used for the prevention and treatment of CVD may cause, exacerbate, or relieve neuropsychiatric symptoms.AimUse Mendelian randomisation (MR) analysis to investigate the potential effect of different antihypertensive drugs on schizophrenia, bipolar disorder and major depressive disorder.MethodsWe conduct two sample MR using expression quantitative trait loci (eQTLs) for antihypertensive drug target genes as genetic instruments, together with summary data from published genome-wide association studies, to investigate the causal effect of changes in drug target gene expression (as proxies of drug exposure) on psychiatric disorders.ResultsA 1 standard deviation lower expression of the ACE gene in blood was associated with 4.0 mmHg (95% CI = 2.7 – 5.3) lower systolic blood pressure, but increased risk of schizophrenia (OR (95% CI) = 1.75 (1.28 – 2.38)). A concordant direction of effect was observed with ACE expression in brain tissue.ConclusionsFindings suggest an adverse effect of lower ACE expression on schizophrenia risk. This warrants further investigation to determine if lowering ACE activity for treatment of hypertension using ACE inhibitors (particularly centrally-acting drugs) may worsen symptoms in patients with schizophrenia, and whether there is any association between ACE inhibitor use and risk of (mainly late-onset) schizophrenia.


Author(s):  
Hanla A. Park ◽  
Sonja Neumeyer ◽  
Kyriaki Michailidou ◽  
Manjeet K. Bolla ◽  
Qin Wang ◽  
...  

Abstract Background Despite a modest association between tobacco smoking and breast cancer risk reported by recent epidemiological studies, it is still equivocal whether smoking is causally related to breast cancer risk. Methods We applied Mendelian randomisation (MR) to evaluate a potential causal effect of cigarette smoking on breast cancer risk. Both individual-level data as well as summary statistics for 164 single-nucleotide polymorphisms (SNPs) reported in genome-wide association studies of lifetime smoking index (LSI) or cigarette per day (CPD) were used to obtain MR effect estimates. Data from 108,420 invasive breast cancer cases and 87,681 controls were used for the LSI analysis and for the CPD analysis conducted among ever-smokers from 26,147 cancer cases and 26,072 controls. Sensitivity analyses were conducted to address pleiotropy. Results Genetically predicted LSI was associated with increased breast cancer risk (OR 1.18 per SD, 95% CI: 1.07–1.30, P = 0.11 × 10–2), but there was no evidence of association for genetically predicted CPD (OR 1.02, 95% CI: 0.78–1.19, P = 0.85). The sensitivity analyses yielded similar results and showed no strong evidence of pleiotropic effect. Conclusion Our MR study provides supportive evidence for a potential causal association with breast cancer risk for lifetime smoking exposure but not cigarettes per day among smokers.


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